leejunhyeok commited on
Commit
828fc93
1 Parent(s): 6b0c101

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +6 -1
README.md CHANGED
@@ -7,13 +7,18 @@ metrics:
7
  - accuracy
8
  library_name: pytorch
9
  ---
 
 
 
 
 
10
  # **Introduction**
11
  MoMo-72B-lora-1.8.7-DPO is trained via Direct Preference Optimization([DPO](https://arxiv.org/abs/2305.18290)) from [MoMo-72B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4) as its base model, with several optimizations in hyperparameters.
12
  [MoMo-72B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4) is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model.
13
  Note that we did not exploit any form of weight merge.
14
  For leaderboard submission, the trained weight is realigned for compatibility with llama.
15
  MoMo-72B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https://moreh.io/product), which simplifies the training of large-scale models, and AMD's MI250 GPU.
16
-
17
 
18
  ## Details
19
  ### Used Librarys
 
7
  - accuracy
8
  library_name: pytorch
9
  ---
10
+
11
+ # 24/04/05 update
12
+ We introduce [modelhub](https://model-hub.moreh.io/), an ai model host platform powered by AMD MI250 GPUs.
13
+ You can now test live-inference of this model at model hub.
14
+
15
  # **Introduction**
16
  MoMo-72B-lora-1.8.7-DPO is trained via Direct Preference Optimization([DPO](https://arxiv.org/abs/2305.18290)) from [MoMo-72B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4) as its base model, with several optimizations in hyperparameters.
17
  [MoMo-72B-LoRA-V1.4](https://huggingface.co/moreh/MoMo-72B-LoRA-V1.4) is trained via Supervised Fine-Tuning (SFT) using [LoRA](https://arxiv.org/abs/2106.09685), with the QWEN-72B model as its base-model.
18
  Note that we did not exploit any form of weight merge.
19
  For leaderboard submission, the trained weight is realigned for compatibility with llama.
20
  MoMo-72B is trained using **[Moreh](https://moreh.io/)**'s [MoAI platform](https://moreh.io/product), which simplifies the training of large-scale models, and AMD's MI250 GPU.
21
+ #
22
 
23
  ## Details
24
  ### Used Librarys